An Approach for Database Intrusion Detection Based on the Event Sequence Clustering
暂无分享,去创建一个
[1] LiaoYihua. Use of K-Nearest Neighbor classifier for intrusion detection11An earlier version of this paper is to appear in the Proceedings of the 11th USENIX Security Symposium, San Francisco, CA, August 2002 , 2002 .
[2] Geert Wets,et al. Discovering Interesting Navigations on a Web Site Using SAMI , 2003, ITWP.
[3] Yi Hu,et al. A data mining approach for database intrusion detection , 2004, SAC '04.
[4] Zhu Yangyong,et al. DNA Sequence Data Mining Technique , 2007 .
[5] V. Rao Vemuri,et al. Use of K-Nearest Neighbor classifier for intrusion detection , 2002, Comput. Secur..
[6] Arindam Banerjee,et al. Clickstream clustering using weighted longest common subsequences , 2001 .
[7] Karthikeyan Ramasamy,et al. Set Valued Attributes , 2005, Encyclopedia of Database Technologies and Applications.
[8] Xiangyang Li,et al. A supervised clustering algorithm for computer intrusion detection , 2005, Knowledge and Information Systems.
[9] Pirjo Ronkainen,et al. Attribute Similarity and Event Sequence Similarity in Data Mining , 1998 .
[10] Pan Ding,et al. Similarity Discovery Techniques in Temporal Data Mining , 2007 .
[11] Tadeusz Morzy,et al. Scalable Hierarchical Clustering Method for Sequences of Categorical Values , 2001, PAKDD.